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Approximating multilinear monomial coefficients and maximum multilinear monomials in multivariate polynomials

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Abstract

This paper is our third step towards developing a theory of testing monomials in multivariate polynomials and concentrates on two problems: (1) How to compute the coefficients of multilinear monomials; and (2) how to find a maximum multilinear monomial when the input is a ΠΣΠ polynomial. We first prove that the first problem is #P-hard and then devise a O (3n s(n)) upper bound for this problem for any polynomial represented by an arithmetic circuit of size s(n). Later, this upper bound is improved to O (2n) for ΠΣΠ polynomials. We then design fully polynomial-time randomized approximation schemes for this problem for ΠΣ polynomials. On the negative side, we prove that, even for ΠΣΠ polynomials with terms of degree ≤2, the first problem cannot be approximated at all for any approximation factor ≥1, nor “weakly approximated” in a much relaxed setting, unless P=NP. For the second problem, we first give a polynomial time λ-approximation algorithm for ΠΣΠ polynomials with terms of degrees no more a constant λ≥2. On the inapproximability side, we give a n (1−ϵ)/2 lower bound, for any ϵ>0, on the approximation factor for ΠΣΠ polynomials. When terms in these polynomials are constrained to degrees ≤2, we prove a 1.0476 lower bound, assuming P≠NP; and a higher 1.0604 lower bound, assuming the Unique Games Conjecture.

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Acknowledgements

An extended abstract of the present paper was reported in Chen and Fu (2010). Negative coefficients in polynomials are first considered in Chen et al. (2012) for monomial testing.

We thank Yang Liu and Robbie Schweller for many valuable discussions during our weekly seminar. We thank Yang Liu for presenting Koutis’ paper (2008) at the seminar. Bin Fu’s research is supported by an NSF CAREER Award, 2009 April 1 to 2014 March 31.

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Correspondence to Zhixiang Chen.

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Chen, Z., Fu, B. Approximating multilinear monomial coefficients and maximum multilinear monomials in multivariate polynomials. J Comb Optim 25, 234–254 (2013). https://doi.org/10.1007/s10878-012-9496-5

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